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  • Good Package for Fitting Polynomial Trend Lines

    - by Rev316
    Given a simple data set, I would like to be able to calculate a trending formula given it's a second order polynomial regression. In fact, it would be great if one could even forecast X periods during calculation (similar to what Excel does). I'm looking for a portable C/C++ package that's relatively easy to use, and allows it to spit out the "best-fit" (highest R^2 value) curve. Any suggestions? Thanks!

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  • Variable sized packet structs with vectors

    - by Rev316
    Lately I've been diving into network programming, and I'm having some difficulty constructing a packet with a variable "data" property. Several prior questions have helped tremendously, but I'm still lacking some implementation details. I'm trying to avoid using variable sized arrays, and just use a vector. But I can't get it to be transmitted correctly, and I believe it's somewhere during serialization. Now for some code. Packet Header class Packet { public: void* Serialize(); bool Deserialize(void *message); unsigned int sender_id; unsigned int sequence_number; std::vector<char> data; }; Packet ImpL typedef struct { unsigned int sender_id; unsigned int sequence_number; std::vector<char> data; } Packet; void* Packet::Serialize(int size) { Packet* p = (Packet *) malloc(8 + 30); p->sender_id = htonl(this->sender_id); p->sequence_number = htonl(this->sequence_number); p->data.assign(size,'&'); //just for testing purposes } bool Packet::Deserialize(void *message) { Packet *s = (Packet*)message; this->sender_id = ntohl(s->sender_id); this->sequence_number = ntohl(s->sequence_number); this->data = s->data; } During execution, I simply create a packet, assign it's members, and send/receive accordingly. The above methods are only responsible for serialization. Unfortunately, the data never gets transferred. Couple of things to point out here. I'm guessing the malloc is wrong, but I'm not sure how else to compute it (i.e. what other value it would be). Other than that, I'm unsure of the proper way to use a vector in this fashion, and would love for someone to show me how (code examples please!) :) Edit: I've awarded the question to the most comprehensive answer regarding the implementation with a vector data property. Appreciate all the responses!

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  • Smoothing Small Data Set With Second Order Quadratic Curve

    - by Rev316
    I'm doing some specific signal analysis, and I am in need of a method that would smooth out a given bell-shaped distribution curve. A running average approach isn't producing the results I desire. I want to keep the min/max, and general shape of my fitted curve intact, but resolve the inconsistencies in sampling. In short: if given a set of data that models a simple quadratic curve, what statistical smoothing method would you recommend? If possible, please reference an implementation, library, or framework. Thanks SO!

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